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2021 | OriginalPaper | Buchkapitel

Research on Classification of Vehicle Driving

Pavement Characteristics Based on Intelligent Perception

verfasst von : Shuang Chen, Ziyang Zhu, Yuan Wang, Xiaozhen Qu, Yang-shan Tang

Erschienen in: Proceedings of China SAE Congress 2019: Selected Papers

Verlag: Springer Singapore

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Abstract

The current research direction of active suspension is primarily focused on the design of feedback control based on pavement information, whilst research effort in actively detecting driving pavement information is rarely put in. Good pavement information recognition system is especially important for the development of suspension technology. This text adopts the binocular vision system to obtain the road two-dimensional image. Firstly, the Semi-Global Block Matching(SGBM)is used for stereo matching and three-dimensional reconstruction. Secondly, the “cleansing” algorithm is then used to remove the erroneous data points in the road vertical contour model. Finally, Multi-class support vector machines (SVM) are trained by using road feature data sets. Vector machine. The research results show that the road two-bit image acquired by the binocular vision system can provide the road surface feature basis for the control of the active suspension system and classification model of road feature data set training can also extract useful information from road images and classify them correctly.

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Metadaten
Titel
Research on Classification of Vehicle Driving
verfasst von
Shuang Chen
Ziyang Zhu
Yuan Wang
Xiaozhen Qu
Yang-shan Tang
Copyright-Jahr
2021
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-7945-5_38

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